Development of molecular-solvent interaction descriptors to improve accuracy of Quantitative Structure Retention Relationship models

最先进的色谱保留预测依赖于商业上可用的分子描述符，如VolSurf+3D、Dragon、MoE。这些描述符可用于评估分子结构-活性或结构-性质关系，以及用于分子数据库的相似性分析和高通量筛选。用于计算这些描述符的算法通常不考虑色谱柱流动相的组成。例如，色谱流动相通常由缓冲液/有机溶剂混合物组成，它们会影响分析物的离子状态，并增强或抑制与固定相的特定相互作用。虽然疏水相互作用是主要的保留机制，但通常是次级相互作用决定了结构相似的化合物的洗脱顺序。该建议的目标包括开发性能优于当前可用选择的新型分子描述符：a)考虑更类似于色谱流动相的介质；b)考虑离子对与含水缓冲组分；c)区分异构体化合物，例如位置异构体或非对映异构体；将使用分子液体积分方程式理论(IETML)开发溶剂化描述符。IETML是一个来自统计力学的溶剂化模型，它提供了丰富的准确的溶液阶段数据，并且对于高通量筛选来说足够快。该方法隐含地区分了同分异构体，适用于广泛的纯/混合溶剂体系，包括那些含有离子物种的体系。它已成功地用于计算类药物分子的溶剂化自由能、渗透率、溶解度、分配系数和结合自由能。Rev.，2015,115,6312]。对于不同溶剂组成和温度的基质，将计算每个分析物的溶剂化自由能密度函数和热力学参数。这些溶剂化描述符将被用来训练新的定量结构保留关系模型(QSRR)。我们将遵循类似于用于预测Caco-2渗透率的过程[Mol.PharmPharmtics，2015，12,3420]，但要根据色谱溶剂系统和环境条件进行调整。由该大学开发的所有软件包将在项目结束时提供给辉瑞。

State of the art predictions of chromatographic retention rely on commercially available molecular descriptors such as VolSurf+3D, Dragon, MOE. These descriptors can be used to evaluate molecular structure-activity or structure-property relationships, as well as for similarity analysis and high-throughput screening of molecule databases. The algorithms that are used to calculate these descriptors usually do not take the composition of chromatographic mobile phase into account. For example, chromatographic mobile phase often consists of buffer/organic solvent mixtures which affect the ionic state of analytes and enhance or suppress specific interactions with the stationary phase. Although hydrophobic interactions are the primary retention mechanism, it is often the secondary interactions which determine the elution order of structurally similar compounds. The objectives of this proposal include the development of novel molecular descriptors that outperform currently available options by virtue of: a) considering a medium more comparable with the chromatographic mobile phaseb) taking into consideration ion pairing with aqueous buffer componentsc) differentiating between isomeric compounds e.g. positional isomers or diastereomers Solvation descriptors will be developed using the integral equation theory of molecular liquids (IETML). IETML is a solvation model from statistical mechanics that provides a wealth of accurate solution-phase data, and is fast enough for high-throughput screening. The method implicitly differentiates between isomeric compounds, and is applicable to a wide-range of pure/mixed solvent systems, including those containing ionic species. It has been used successfully to compute solvation free energies, permeabilities, solubilities, partition coefficients, and binding free energies of druglike molecules [Chem. Rev., 2015, 115, 6312]. Solvation free energy density functions and thermodynamic parameters will be computed for each analyte for a matrix of different solvent compositions and temperatures. These solvation descriptors will be used to train novel Quantitative Structure Retention Relationship models (QSRR). We will follow a procedure similar to one used to predict Caco-2 permeability [Mol. Pharmaceutics, 2015, 12, 3420], but adapt it to chromatographic solvent systems and environmental conditions. All software packages that are developed by the University will be provided to Pfizer at the end of the project.